Expression of cardiac GATA4 and downstream genes after exercise training in the db/db mouse
Bibliographic record
Abstract
GATA4 is a transcriptional factor expressed in heart that regulates the synthesis of structural and cardioprotective genes. We have demonstrated that low GATA4 expression in the db/db mouse heart is associated with reduced expression of key downstream genes, including oxytocin (OT) natriuretic peptide (A-, B-type), nitric oxide synthase (eNOS), and myosin heavy chain (α-MHC). In this study, the effect of exercise on GATA4 expression and related genes was determined in the db/db mouse, a model that represents human type 2 diabetes. Vascular endothelial growth factor (VEGF) and hypoxia-induced factor-α expression were also measured after 8 weeks of treadmill running. Compared with control littermates, db/db mice exhibited hyperglycemia and obesity, and exercise failed to improve these parameters. GATA4 expression was reduced in db/db hearts and this was associated with reduced expression of OT, OTR, ANP, BNP, eNOS, α-MHC, and ratio of α- to β-MHC, whereas mRNA expression of β-MHC and VEGF remained unchanged compared with control hearts. Exercise training increased GATA4 expression (mRNA and protein) but most genes regulated by GATA4 were not observed to increase accordingly. However, protein expression of eNOS, mRNA expression of α-MHC, ratio of α- to β-MHC, and protein expression of VEGF were increased in db/db hearts after exercise. In conclusion, while GATA4 expression is increased following exercise, not all structural and cardioprotective genes are expressed, suggesting other transcription factors may be involved in this regulation. Regardless of this effect, the positive effect of exercise training on key protective genes is evident in the db/db mouse heart.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".